Prediction of Lymphatic Metastasis in Esophageal Cancer by CT Radiomics

Peking University Cancer Hospital & Institute

Status: Completed

Conditions: Esophagus Cancer

Treatments: Procedure: preoperative enhanced chest CT examination

Study type: Observational

Funder types: Other

Identifiers

NCT03237130

CTRadiomics-LMesophagus-BNSF

Details and patient eligibility

About

This study proposes to establish a CT radiomics-based prediction model for identifying metastasis lymph nodes in esophageal cancer.

Full description

This study proposes to establish an image feature extraction and selection method for identifying lymph node metastasis of esophageal cancer.The study will consider the relationship between the main lesion and the suspected lymph node, extract association characteristics in order to improve the sensitivity and specificity of the CT radiomics-based prediction model for identifying metastasis lymph nodes. The study includes the construction of CT radiomics-based prediction model and the validation of the prediction model.

Enrollment: 133 patients

Sex: All

Volunteers: No Healthy Volunteers

Inclusion criteria

• pathologically proven esophageal cancer
• scheduled to preoperative enhanced chest CT and undergo surgery
• sign the patient informed consent

Exclusion criteria

• failed to receive preoperative enhanced chest CT or undergo surgery
• inavailable pathological results for local lymph node status
• inquality of CT images for feature extraction
• patient quit

Trial design

133 participants in 1 patient group

preoperative enhanced chest CT

Description:

The cohort contains patients with preoperative therapies and patients without preoperative therapies. Each patient receives regular preoperative enhanced chest CT; for patients with preoperative therapies, they usually undergo twice enhanced chest CT examination at before and after preoperative therapies, the CT images after preoperative therapies will be used for analysis

Treatment:

Procedure: preoperative enhanced chest CT examination